Abstract

Aging refers to the processes by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soils decline overtime. We studied the characteristics of the aging process in copper (Cu) added to soils and the factors that affect this process. Then we developed a semi-mechanistic model to predict the lability of Cu during the aging process with descriptions of the diffusion process using complementary error function. In the previous studies, two semi-mechanistic models to separately predict short-term and long-term aging of Cu added to soils were developed with individual descriptions of the diffusion process. In the short-term model, the diffusion process was linearly related to the square root of incubation time (t1/2), and in the long-term model, the diffusion process was linearly related to the natural logarithm of incubation time (lnt). Both models could predict short-term or long-term aging processes separately, but could not predict the short- and long-term aging processes by one model. By analyzing and combining the two models, we found that the short- and long-term behaviors of the diffusion process could be described adequately using the complementary error function. The effect of temperature on the diffusion process was obtained in this model as well. The model can predict the aging process continuously based on four factors—soil pH, incubation time, soil organic matter content and temperature.

Highlights

  • The term “aging” refers to the process by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soil decline over time

  • The diffusion process of aging is strongly influenced by incubation time; it shows a reliance on temperature as well

  • Donner et al [36] found that very rapid reactions (

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Summary

Introduction

The term “aging” refers to the process by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soil decline over time. This process is occasionally referred to as “natural attenuation” or “fixation” [1,2]. Ma et al [27,28] developed two models to predict the lability of Cu in short-term and long-term aging separately using different descriptions of the diffusion process. We developed a new semi-mechanistic model to predict the lability of Cu during aging based on above three known processes, with description of diffusion process using complementary error function. The model was validated by testing against 19 soil samples from different European countries with a wide range of physiochemical properties, and the results showed that the model successfully predicted the lability of Cu added to soils

Soil samples and treatments
Determination of Cu lability
Modeling of Cu lability
Results and discussion
Determination and analysis of parameters in erfc model
Validation of the model
Conclusion
Full Text
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